Tissue-specific profiling of age-dependent miRNAomic changes in Caenorhabditis elegans

Ageing exhibits common and distinct features in various tissues, making it critical to decipher the tissue-specific ageing mechanisms. MiRNAs are essential regulators in ageing and are recently highlighted as a class of intercellular messengers. However, little is known about the tissue-specific transcriptomic changes of miRNAs during ageing. C. elegans is a well-established model organism in ageing research. Here, we profile the age-dependent miRNAomic changes in five isolated worm tissues. Besides the diverse ageing-regulated miRNA expression across tissues, we discover numerous miRNAs in the tissues without their transcription. We further profile miRNAs in the extracellular vesicles and find that worm miRNAs undergo inter-tissue trafficking via these vesicles in an age-dependent manner. Using these datasets, we uncover the interaction between body wall muscle-derived mir-1 and DAF-16/FOXO in the intestine, suggesting mir-1 as a messenger in inter-tissue signalling. Taken together, we systematically investigate worm miRNAs in the somatic tissues and extracellular vesicles during ageing, providing a valuable resource to study tissue-autonomous and nonautonomous functions of miRNAs in ageing.

[Internet] Elsevier; 2023; Available from: hftps://www.cell.com/cell-reports-methods/pdf/S2667-2375(23)00103-0.pdfReviewer #2 (Remarks to the Author): This study profiled age-dependent changes in transcriptome, miRNAome expression across five somafic fissues in the nematode C. elegans.The author also profiled EVs composifion and idenfified several miRNAs present in EVs not transcribed in other fissues.The author tested one of them (miR-1) and its relafionship with the intesfine gene DAF-16.The results of this analysis and the main experiments shown let the author conclude that many miRNAs are indeed transported from one fissue to another during the worm's lifespan.
This very interesfing topic is not novel, but this study provides an updated view of the crosstalk between EV miRNAs and somafic fissue miRNAs.Overall, the manuscript is good, but it lacks wet-bench validafion throughout it.In addifion, some of the figures and tables need to be revised to convey their message befter.

Major issues:
• Similar transcriptomes and miRNA isolafion techniques have been used in the past and must be used as a comparison.Compare miRNA data with Schorr et al., 2023 and Serizay et al, 2020 and Alberfi et al.

2018.
• Where is the raw data used to generate Figure 3? Did the author prepare the 65 promoter::GFP constructs, prepare transgenic strains and study their fluorescence paftern?Did they use previously published data?This is unclear and needs to be addressed.
• In the discussion secfion, Figure 3 shows 19 miRNAs with a PmiR:GFP signal but no miRNA-seq signal.The authors should compare the expression of these miRNAs in other published datasets.
• In Extended Data Figure 3d, some of the PITT-miRs not detected in EVs have high UMIs.Why are these highly expressed PITT-miRs not being detected in EVs?
• Technical issue: Are there similarifies among the cells used for each fissue?The principal component analysis suggests that.The mechanical separafion used by the authors may have released the same cells in each fissue, which may not be a good representafive of each fissue's complexity itself.This point at least needs to be menfioned in the discussion secfion.
• Figure 4 is misleading because the author only sequenced five fissues and did not have a global transcriptome/miRNAome for all fissues.It could be that a given miRNA is transported from a different fissue not sequenced by the authors.
• The model proposed by the author is fascinafing but is not adequately discussed in the discussion secfion.Do worm somafic cells have a check in place for each fissue to absorb only one kind of EV containing specific miRNAs?This is highly unlikable, and its funcfion needs to be adequately discussed and speculated in the discussion secfion.
• It is unclear how EVs were isolated.In the method secfion, the authors menfioned QIAzol, which is used to isolate total RNAs and differenfial centrifuges.Could there be contaminafion from total RNAs, which is not representafive of EV RNAs?This crifical step needs to be explained in the method secfion.
• The author did not address from which fissue EVs were released.This inifial part of the manuscript is purely bioinformafics, with no wet bench validafion.
• The daf-16/miR-1 secfion is very nice, but the author did not show the crifical point that miR-1 found in the intesfine is of muscle fissue origin.Although transcribed in the muscle, several studies found this miRNA also in other fissues.Perhaps the author could label muscle miRNAs and see if they detect in the intesfine (mime-seq?).
• Is there an enrichment of age-related targets for Age-DEMIRs?Please repeat this analysis with non-Age-DEMIRs and include it in Figure 6c.
• Figure 7a does not offer much insight into how inter-fissue miRNA signaling regulates aging.Please replace it with a figure or table showing which mRNAs are targeted by PITT-miRs in day 1 worms and in day 8 worms (and if there is any difference between these two groups).

Minor issues:
• The legend for Figures 6a and 6b must be in separate paragraphs.
• Figure 6b does not offer much insight into how miRNAs regulate aging.Please replace it with a figure or table showing which mRNAs are targeted by miRNAs in day 1 worms and day 8 worms (and if there is any difference between these two groups).
• In Extended Data Figure 3d, many PITT-miRs not detected in EVs appear to have a mean UMI of 0. However, the shown threshold for expression (and thus inclusion in your analyses) is a UMI sum of 10.Is this a byproduct of how this figure was made?
• Extended Data Table 2 is unclear and does not explain how fissue-specific miRNAomes change during aging.Please revise this table by including the specific EV miRNAs that changed with age.
We are grateful to the reviewers for their time and efforts on our manuscript.We appreciate their insightful and constructive comments.Below is our point-to-point response.
Our replies in the rebuttal letter and corresponding modifications in the revised main text are marked in blue.

REVIEW NCOMMS-23-20619
The manuscript: "Tissue-specific profiling of age-dependent miRNAomic changes in Caenorhabditis elegans" is conceptually very interesting.For the main claims of this manuscript -inter-tissue trafficking as measured by the lack of transcription but the presence of microRNAs -however, I see substantial shortcomings.Many aspects of the study are too briefly explained and conclusions too bold in the light of the presented analyses /results.

Use of miRBase:
For years, a major concern in microRNA research has been the quality of the online repository miRBase (1-14) with estimates of 2/3 false-positive entries.Thus, the database contains many false-positives and not only microRNAs.These are for instance numerous tRNA, rRNA or other fragments and transcriptional noise but also incorrectly annotated bona fide miRNAs that strongly influence interpretations of data.In addition to the false positives, miRBase annotations are often imprecise and have varying precursor annotation forms (with or without flanking regions of varying lengths) and very often not both arms are annotated, 3' ends are incorrect, and in a few cases even 5' are not correctly annotated which substantially affects target predictions, and more so, in this case here when needing accurately defined Drosha and Dicer cutting sites.
Further it is using an outdated nomenclature which is inconsistent and leads to problems of not-summarizing inconsistently named miRNAs.This all has been addressed in the manually curated microRNA gene database MirGeneDB.org(15)(16)(17) → authors should repeat their analyses with MirGeneDB set of microRNAs for C. elegans --As suggested, all our analyses have been re-performed by the C. elegans miRNAs curated in MirGeneDB 2.1.In our previous analysis of inter-tissue miRNA signalling, only miRNAs with high confidence were considered.These miRNAs are all in MirGeneDB, except for one miRNA.So, our conclusions of inter-tissue miRNA signalling are barely affected.Highlight commonly deregulated microRNAs --Thank you for your suggestion!The Age-DEMIRs shared in multiple tissues are listed in the revised Extended Data Table 1 (sheet: 'shared across tissues').

Deregulation reporting
Check microRNA families --The information of microRNA families has been included in the revised Extended Data Table 1.

Linking absence of transcription to inter-tissue transport
The authors state absence of detection of transcription equals the actual lack of transcription.
Can the authors rule out that in fact leaky transcription takes place?--We analysed transcription using PmiR::GFP reporters.Due to the sensitivity of these reporters, we can hardly rule out that in fact leaky transcription could take place.Therefore, we have not stated that absence of detection of transcription equals the actual lack of transcription.We further clarified this issue in the revised manuscript.
Our datasets suggest that a group of miRNAs are highly likely to be transported across worm tissues by the discrepancies in their PmiR::GFP and miRNA-Seq signals.We term them as PITT-miRNA (Potentially Inter-Tissue Transported miRNA).
Studies of cell lines in human (18) and isolated cell-types in CEL (19) have in depth measured microRNAs.Could the authors use these cell-lines to study the presence of non-transcriptionally active microRNA transcripts?
This has consequences for the EV-work.
--There are extensive studies on secreted miRNAs in EV, using cultured cell lines (including human cell lines).Based on these studies, it is now well-accepted that EVcapsulated miRNAs are inter-cellular messengers (Maas et al., 2017).However, little is known about the scale of inter-tissue miRNA signalling, which are potentially mediated by EV, in a living organism.To address this issue, this manuscript aims at providing a global picture of inter-tissue miRNA signalling, not only at an organismal (C.elegans) level but also from a miRNAomic perspective.
To achieve this goal, we did use freshly isolated worm cells, although not worm cell lines, to profile tissue-specific miRNAomes (Figure 1).Combined with a systematic analysis of PmiR::GFP signal in worm tissues, we then mapped the inter-tissue miRNA trafficking network based on PITT-miRs (Figure 3 and 4).Our previous report on mir-83 (Zhou et al., 2019) and the mir-1-related studies in this manuscript (Fig. 8 and Extended Data Fig. 7) provide further evidence to support this network.

Please discuss and also check isomir content (but see (20))
--The IsoSeek method, as employed in reference 20, utilizes a randomized-end adapter strategy to mitigate ligation bias, thereby enabling the detection of isomiRs.
Several analogous methods have been developed since 2015, such as 4N-seq and AQseq.While this approach is powerful, none of these techniques are capable of profiling small RNAs using < 1 ng of total RNA.In our study, our small RNA library construction relies on a minute sample of approximately 20 cells, equivalent to 100-200 pg of total RNA.Consequently, we were unable to employ the randomized-end adapter-based method to assess and quantify isomiR content.We acknowledge that the inclusion of isomiR-related information in our study could provide valuable insights into the functional roles of miRNAs in aging.We remain optimistic that ongoing advancements in small RNA sequencing methodologies will eventually overcome this limitation, broadening the scope of such research.In the revised manuscript, we discuss the isomiR issue as suggested.Please see page 6 and 23 for details.

Evolutionary interpretations
The authors should attempt to compare the evolutionary age of all microRNAs they find to be age-indicative (which can easily be done in MGDB).
--Thank you for your suggestion!In the revised manuscript, we labelled the evolutionary age of all examined microRNAs in Extended Data Table 1 by the information in MirGeneDB.
Discuss the indicative evolutionary age for the mechanisms the authors proposed.
--The evolutionary age of Age-DEMIRs does not show a clear difference from that of all detected miRNAs.Of interest, PITT-miRs are modestly older in evolution than all detected miRNAs, suggesting that inter-cellular miRNA trafficking could be an ancient way of cell-to-cell communication.Corresponding discussion has been included in the revised manuscript.Please see page 19 for details.
• In Extended Data Figure 3d, some of the PITT-miRs not detected in EVs have high UMIs.Why are these highly expressed PITT-miRs not being detected in EVs? --Good question!We think this shows that there could be other ways for miRNAs to be transported across tissues.According to previous reports, circulating RNAs are not necessarily EV-associated (Cui et al., 2019;Kumar and Reddy, 2016).Corresponding discussion has been included in the revised discussion section.Please see page 19 for details.
• Technical issue: Are there similarities among the cells used for each tissue?The principal component suggests that.
--We appreciate your notice of this similarity.Although these cells are from different tissues, they should share some basic biological processes.In fact, our previous report on tissue-specific mRNA transcriptomes clearly shows this fact (Wang et al., 2022).The gene set enrichment analysis (WormCat) in this study also indicate that miRNAs in distinct tissues are regulating some common activities.In the revised manuscript, we have further clarified this issue in the revised manuscript.Please see page 7 for details.
The mechanical separation used by the authors may have released the same cells in each tissue, which may not be a good representative of each tissue's complexity itself.This point at least needs to be mentioned in the discussion section.
--It is a feature of C. elegans tissues, except for neurons and germline, that they consist of highly homogeneous cells.Therefore, the dozens of hand-picked cells from intestine, body wall muscle, hypodermis, and coelomocytes can well represent these tissues.For neurons, we collected thousands of neurons following the protocol established by Murphy lab (Kaletsky et al., 2015).Given the number of analysed neurons in this study, our neuronal dataset should cover different types of worm neurons and be representative of this tissue.
Yet, we also agree with the reviewer that the highly homogeneous cells in a worm tissue could still have slight variations.Corresponding discussion have been added in the revised manuscript.Please see page 17.
• Figure 4 is misleading because the author only sequenced five tissues and did not have a global transcriptome/miRNAome for all tissues.It could be that a given miRNA is transported from a different tissue not sequenced by the authors.
--We appreciate your notice of this possibility that a given miRNA could be transported from a non-sequenced tissue into the five analysed ones.In our initial submission, we showed this situation in Figure 4 with brown arrows, although without highlighting.In the revised manuscript, we further clarified this issue in the Result and Discussion sections (page 10 and 20), Figure 4 and its legend.
• The model proposed by the author is fascinating but is not adequately discussed in the discussion section.Do worm somatic cells have a check in place for each tissue to absorb only one kind of EV containing specific miRNAs?This is highly unlikable, and its function needs to be adequately discussed and speculated in the discussion section.
--Many thanks for your appreciation of our model!We have included the suggested issues in the revised Discussion section.Please see page 20 for details.
• It is unclear how EVs were isolated.In the method section, the authors mentioned QIAzol, which is used to isolate total RNAs and differential centrifuges.Could there be contamination from total RNAs, which is not representative of EV RNAs?This critical step needs to be explained in the method section.
--Sorry for the confusion!We isolated EVs secreted by worms following the established protocol reported by both us and Kaeberlein lab (Russell et al., 2020;Zhou et al., 2019).In brief, worms were cultured in M9 buffer for 6 h.While the sedimented worms were collected as worm samples, the supernatant was subjected to ultracentrifugation to isolate the EVs secreted from worms.QIAzol was used in the subsequent RNA preparations for both worm and EV samples.Therefore, it is highly unlikely that there is any contamination from worm total RNAs in EV RNAs.We have further clarified this critical issue in the Method section as suggested.
Please see page 26 for details.
• The author did not address from which tissue EVs were released.
--As mentioned above, we collected EVs secreted from worms.Therefore, we are unclear which tissues EVs are from.That is why we compared the miRNAome in EV with that in the whole worm (Figure 5), but not with those in specific worm tissues.
We agree with the reviewer that it is interesting to map the precise source tissues of these EVs.It is likely that different tissues could secrete distinct EVs.Although it is now hard to address this issue due to technical hinderances, we believe it will be a fascinating and critical topic to pursue in the future.Corresponding discussion has been included in the revised manuscript.Please see page 21 for details.This initial part of the manuscript is purely bioinformatics, with no wet bench validation.
• The daf-16/miR-1 section is very nice, but the author did not show the critical point that miR-1 found in the intestine is of muscle tissue origin.Although transcribed in the muscle, several studies found this miRNA also in other tissues.Perhaps the author could label muscle miRNAs and see if they detect in the intestine (mime-seq?).
--Using a transgene expressing miR-1 specifically in body wall muscle and a mutant worm strain knocked out of the endogenous mir-1 gene, we detected muscle-derived miR-1 in intestine by RT-qPCR (Extended Data Fig. 7b).Although we did not analyse other tissues, we believe that miR-1 in other non-muscle tissues, as the reviewer mentioned, is likely to be of muscle origin, by our inter-tissue miRNA analysis (Figure 3 and 4).
• Is there an enrichment of age-related targets for Age-DEMIRs?Please repeat this analysis with non-Age-DEMIRs and include it in Figure 6c.
--By the genes reported in GenAge, we do not observe an enrichment of age-related targets for Age-DEMIRs.The ratio of GenAge-curated genes in Age-DEMIR targets is similar to that in non-Age-DEMIR targets across the five examined tissues (Table 1

Figure 1
Figure1is poor and should be improved: for reviewer).